Letting in the Sunshine: The Problem of Transparency in Algorithmic Governance

-- By JackFurness - 16 Apr 2021

Algorithmic Governance

Algorithms have already infiltrated nearly every aspect of modern life. Blockchain-based applications, which have already revolutionized the global financial industry by reducing friction within and between capital markets, will soon form the basis of decentralized communication platforms, self-enforcing “smart contracts,” and perhaps even politics or law. While this new era of decentralization offers exciting potential for the creation of new forms of digital rights management, machine learning has the potential to work harms as well. This paper discusses the rise of algorithmic governance—government by computer—and explains how the First Amendment might require greater transparency by government actors.

How the Government Relies on Algorithms

Algorithmic governance refers to the use of autonomous decisionmaking methodologies by governments to replace traditional deliberation. At a high level of generality, an algorithm is simply a set of steps in a mathematical or logical process. In the sense then that algorithmic government promises efficiency and accuracy there is nothing new or problematic about its use. When the U.S. Postal Service uses machine learning to sort mail, for example, no serious constitutional concerns arise.

Algorithms may be employed to influence everything from policymaking to policing to even the adjudicative process. A society could even, through the use of smart-contracts, allow its citizens to create customized legal systems, what some have referred to as “digital common law.” More moderate forms of digital governance are already widespread. As algorithms promise of efficiency and accuracy at a lower cost than ever before, the role of machine learning in our government has plenty of room to grow.

The Transparency Problem

“Sunlight,” the saying goes, “is said to be the best of disinfectants.” Transparency is an essential component of ordered government and fair, open societies. Algorithms, when shielded by claims of proprietorship and trade secrets, can lead to oppression. Without transparency there can be no accountability.

Machine Learning and the Potential for Abuse

Current and future applications of machine learning deployed by the government raise important questions about the transparency of algorithmic governance. While most governmental applications of machine learning are not outcome determinative but simply one piece in a larger decisionmaking process, the potential for fully automated governance is not difficult to imagine. For example, the government can easily use a high speed camera and a simple algorithm to detect and ticket speeding drivers without any human input. In this example, the algorithmic process plays only a minor role. A litigant wishing to challenge the legality of this process would likely have no need of knowing how the camera calculated their speed unless it is clear that the camera malfunctioned. But suppose that the judge who presides over the traffic court is replaced by a computer that automatically determines culpability on the basis of an offender’s digital profile. It is easy to see how a system like this could be problematic from a constitutional perspective. And yet, there is no principled reason to believe that the government will regulate its own behavior in this area. Therefore, litigants need access to as many tools as possible in challenging unconstitutional invasions of privacy. The first and most important instrument in this toolkit is transparency.

What Must the Government Share and When?

Laws regulating government transparency mandate public access to a wide array of federal government activity, from the public nature of most legislative activity to the requirement that agencies publish notes of proposed regulations. Moreover, the principle of reasoned transparency, rooted in the due process protections of the Fifth and Fourteenth Amendments, requires the government in some cases to provide explanations for why it is taking a particular course of action.

Open Access: A Solution to Closeted Decisionmaking

Algorithms are here to stay, but the extent to which litigants and observers can access to government algorithms to probe their legality is far from settled. First Amendment doctrine protects the speech rights of citizens, but also includes the freedom to access information and ideas. The growing prevalence and invasiveness of algorithmic government will likely raise difficult questions about the reach of this doctrine.

First Amendment Doctrine

The First Amendment demands a certain level of transparency in government decisionmaking. While there is no general “right to know” under the First Amendment, legislation such as the Freedom of Information Act has codified a basic presumption of transparency between the federal government and American citizens. Such a right existed at common law as well.

Right to Access

The First Amendment right to access demands that preliminary criminal hearings be held in open Court. In Press-Enterprise Co. v. Superior Court (“Press-Enterprise II”) and its progeny, the Supreme Court established a presumption of public access to bail hearings and sentencing. Thus, at least to the extent that algorithmic processes are used to generate evidence for use at trial, set bail, or sentence a defendant, the First Amendment requires that these proceedings be conducted in an open and transparent manner. This includes access to decisionmaking algorithms.

Access to computerized algorithms is critical for the fair and efficient functioning of government. For one reason, algorithms can and do make mistakes. Additionally, the potential for human error and cognitive bias to affect how these algorithms are used should be apparent. Suppose, for example, an expert witness in a criminal trial employs a well-known methodology to identify a murder weapon, but that official lacks the training to properly employ the methodology and makes a mistake, causing the wrong weapon to be identified. The process may be sound in theory, but unconstitutional in practice. Transparency permits problems like this to be uncovered. As computers and their programmers are also prone to error, the Press Enterprise II doctrine can and should be extended to allow for greater transparency any time an algorithm is used in the criminal context.

The Experience and Logic Test

The prevailing test for evaluating when the right to access applies is the “experience and logic test,” which states that the public access right attaches to any judicial proceeding (1) historically open to the public (2) that would benefit from access and oversight. There is no shortage of ways in which algorithmic government can transgress this test. As machine learning becomes increasingly prevalent, public access is perhaps the only way to hold the government accountable. Public scrutiny has tangible benefits, while secrecy can lead not only to a higher rate of error, but also public distrust of the legal system.

Letting in the sunshine truly is the best remedy for an overreaching government, and as algorithms continue to supplant traditional decisionmaking roles, transparency is an antidote that we cannot do without.

---

You are entitled to restrict access to your paper if you want to. But we all derive immense benefit from reading one another's work, and I hope you won't feel the need unless the subject matter is personal and its disclosure would be harmful or undesirable. To restrict access to your paper simply delete the "#" character on the next two lines:

• #Set ALLOWTOPICVIEW = TWikiAdminGroup, JackFurness
• #Set DENYTOPICVIEW = TWikiGuest

Note: TWiki has strict formatting rules for preference declarations. Make sure you preserve the three spaces, asterisk, and extra space at the beginning of these lines. If you wish to give access to any other users simply add them to the comma separated ALLOWTOPICVIEW list.